Abstract
Abstract. Knowledge of forest parameters, such as wood volume, is required for a sustainable forest management. Collecting such information in the field is laborious and even not feasible in inaccessible areas. In this study, tree wood volume is estimated utilizing remote sensing techniques, which can facilitate the extraction of relevant information. The study area is the University Forest of Taxiarchis, which is located in central Chalkidiki, Northern Greece and covers an area of 58km2. The tree species under study is the conifer evergreen species P. brutia (Calabrian pine). Three plot surfaces of 10m radius were used. VHR Quickbird-2 images are used in combination with an allometric relationship connecting the Tree Crown with the Diameter at breast height (Dbh), and a volume table developed for Greece. The overall methodology is based on individual tree crown delineation, based on (a) the marker-controlled watershed segmentation approach and (b) the GEographic Object-Based Image Analysis approach. The aim of the first approach is to extract separate segments each of them including a single tree and eventual lower vegetation, shadows, etc. The aim of the second approach is to detect and remove the “noisy” background. In the application of the first approach, the Blue, Green, Red, Infrared and PCA-1 bands are tested separately. In the application of the second approach, NDVI and image brightness thresholds are utilized. The achieved results are evaluated against field plot data. Their observed difference are between -5% to +10%.
Highlights
Wood volume is one of the most important forest parameters and its monitoring is one of the main tasks of regional forest management plans aiming among others to the preservation of the environment, recreation, strengthening the local economy etc
The relative Root-Mean-Square Error (RMSE) was 64% for optical data and 53% combining optical with radar data
An error of 58 to 84% was observed on plot level in the study (Tuominen and Pekkarinen 2005) which was conducted in Finland utilizing airphotos of 0.5 m on tree species of pine, fir and birch
Summary
Wood volume is one of the most important forest parameters and its monitoring is one of the main tasks of regional forest management plans aiming among others to the preservation of the environment, recreation, strengthening the local economy etc. The relative Root-Mean-Square Error (RMSE) was 64% for optical data and 53% combining optical with radar data. An error of 58 to 84% (relative RMSE) was observed on plot level in the study (Tuominen and Pekkarinen 2005) which was conducted in Finland utilizing airphotos of 0.5 m on tree species of pine, fir and birch. LIDAR, CIR (Colour InfraRed) airphotos (0.4 m spatial resolution) and TM satellite imagery were utilized to estimate the wood volume of pines, beeches and oaks in southwest Germany (Latifi et al 2010). ICESat/GLAS and MODIS data were utilized to estimate wood volume for various species such as pines, birch, firs and others in central Siberia (Nelson et al 2009).
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